Andrew R. Wood

The paper identifies 260 genes associated with sleep phenotypes using rare coding variants from large-scale sequencing data, revealing distinct genetic architectures and biological mechanisms across different sleep measurements.

This study uses whole-genome sequencing in 672,976 individuals to show rare and common variants converge in genetic associations for anthropometric traits, with ultra-rare variants explaining less than 10% of heritability.

This study identifies genetic associations for multiple sleep disorders and medications in over 1.6 million individuals, revealing shared and unique genetic factors across sleep traits.

The paper reduces error rates in population-scale whole-genome sequencing by applying genotype-level quality control, demonstrating its effectiveness using UK Biobank and All of Us datasets.

The paper introduces vcf2agds, a toolkit converting WGS data to aGDS format, enabling efficient analysis of UK Biobank data and identifying 480 genome-wide significant associations for total cholesterol.

The paper identifies non-canonical FBN1 splice variants in undiagnosed Marfan syndrome families using genome sequencing and RNA testing, finding 20 candidate variants with significant enrichment in FTAAD cases.

The paper identifies rare genetic variants associated with birth weight, highlighting genes involved in adipose tissue regulation, placental function, and insulin-like growth factor signaling.

This paper develops a polygenic risk score model to predict colorectal cancer risk in symptomatic patients using UK Biobank data, achieving high predictive accuracy.

The paper investigates how rare variants in monogenic developmental disorder genes interact with common variants to affect cognitive and socio-economic traits, finding that higher educational attainment polygenic scores can partially counterbalance adverse effects.

The paper uses whole-genome sequencing data from UK Biobank participants to identify rare non-coding variants and regions associated with circulating protein levels.

The paper identifies individuals deviating from genetically predicted phenotypes using UK Biobank data and shows they are enriched for rare genetic variants and clinical conditions.

This study identifies 118 candidate causal genes and 21 novel lipid loci on the X chromosome through a multi-ancestry meta-analysis of blood lipid levels, revealing sex-biased effects and pleiotropy with cardiovascular and hormonal traits.

The paper estimates penetrance of monogenic diabetes variants across different ascertainment contexts, finding age-related variability for HNF1A/HNF4A variants but consistent penetrance for GCK variants.

This study examines the impact of Mendelian sleep and circadian genetic variants in population cohorts and finds no strong associations with extreme sleep traits, though some variants show minor effects.

This paper integrates GWAS data with functional genomic datasets to identify regulatory mechanisms and causal genes underlying lipid-related traits.

The paper identifies genetic variants linked to ovarian ageing and shows they increase offspring de novo mutation rates, demonstrating heritability of female mutation rate.

The paper investigates the phenotypic effects of rare variants in developmental disorder genes in the general population, finding milder related traits in carriers.

This paper identifies a genetic association between NK3R (TACR3) and menopausal vasomotor symptoms (VMS) using GWAS, while finding no link between rare NK3R variants and VMS despite the efficacy of NK3R antagonists.

This study examines genetic scores for birth weight in South Asians, finding associations with birth size, childhood body size, and adult cardiometabolic markers.

The paper examines the effect of fetal genetic predispositions to metabolically favourable adult adiposity and BMI on birth weight and other anthropometric traits, finding stronger associations with birth weight for the adiposity alleles.

This paper introduces revTWMR, a method to determine causal relationships between gene expression and complex traits, finding that traits more strongly influence gene expression than vice versa.

This study uses Mendelian Randomisation to show that maternal metabolically favourable adiposity is associated with lower offspring birth weight compared to general adiposity indexed by BMI.

This study identifies genetic loci associated with daytime napping and finds potential causal links between napping and cardiometabolic traits.

The paper identifies genetic variants and phenotypes associated with participation in optional UK Biobank components and shows common participation bias across studies.

This study identifies 42 genetic loci associated with excessive daytime sleepiness and links them to phenotypic subgroups and related traits.

This study identifies genetic effects on birth weight and their impact on cardio-metabolic traits, distinguishing fetal and maternal contributions.

The paper identifies 57 genomic regions associated with insomnia symptoms, linking them to phototransduction, ubiquitination, and potential causal relationships with coronary heart disease and depression.